Sensed physiological parameters, and in particular bioelectrical signals (also called "bio-signals") such as brainwaves (EEG) and muscle signals (EMG) have been used to control electrical devices such as lights, music, game boards and children's toys. Previous control methods have relied upon threshold detection schemes wherein the voltage level of a band-limited signal exceeds a certain level (Hartzell et. al., U.S. Pat. No. 4,949,726), or on evoked potentials (Abdallah, U.S. Pat. No. 5,310,195), or on action potentials (Crawford Jr., U.S. Pat. No. 4,158,196). Other previous control methods alternatively calculate the peak power value using a Fast Fourier Transform (the "FFT") and determine whether the peak power exceeds a predefined threshold or the amount by which the threshold is exceeded for control. One drawback of those methods is that the person controlling the devices must learn how to generate particular signals in order to affect control, or must be provided with particular kinds of external stimuli. For example, in an alpha wave controlled system, the subject must learn to relax to reduce the amplitude of the brain (EEG) signals in the 8-12 Hz band. Another drawback of such threshold detection schemes is the susceptibility of the system to spurious signals such as muscle movement, for example, eye movement. Previous methods use specialized dedicated links between the subject and the controlled system.
As a result, there is a need for an improved method and apparatus for detecting and analyzing physiological signals, for utilizing the results of the analysis that does not require significant user training, and for utilizing the results of the analysis for the passive or active control of physical and virtual spaces and the contents therein.